Point Cloud Projection

Label KITTI point cloud (3d) drivable area using provided image annotations (2d). Only tested with Python 3.

• includes a new calibration file reader, tailored to KITTI road calibration files
• includes script label point cloud

How it Works

1. Project point cloud onto the camera, using calibration information.
2. Use image annotations to associate points to labels, drivable or otherwise.
3. Save point cloud with associated labels.

Usage

1. Download the KITTI Road base kit and velodyne.
2. Save data_road and data_road_velodyne in the root directory of this repository.
3. Run the main script, to label the velodyne points using the image 2d annotations. Note that the original velodyne binaries contain nx4 matrices of x,y,z,intensity. The new .npy files will contain nx5 matrices of x,y,z,intensity,drivable, where drivable is a boolean-valued integer.